<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "https://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/>
<meta http-equiv="X-UA-Compatible" content="IE=9"/>
<meta name="generator" content="Doxygen 1.9.1"/>
<meta name="viewport" content="width=device-width, initial-scale=1"/>
<title>Doxygen: pcl::registration::CorrespondenceEstimationNormalShooting&lt; PointSource, PointTarget, NormalT, Scalar &gt; 模板类 参考</title>
<link href="tabs.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="jquery.js"></script>
<script type="text/javascript" src="dynsections.js"></script>
<link href="navtree.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="resize.js"></script>
<script type="text/javascript" src="navtreedata.js"></script>
<script type="text/javascript" src="navtree.js"></script>
<link href="search/search.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="search/searchdata.js"></script>
<script type="text/javascript" src="search/search.js"></script>
<link href="doxygen.css" rel="stylesheet" type="text/css" />
</head>
<body>
<div id="top"><!-- do not remove this div, it is closed by doxygen! -->
<div id="titlearea">
<table cellspacing="0" cellpadding="0">
 <tbody>
 <tr style="height: 56px;">
  <td id="projectalign" style="padding-left: 0.5em;">
   <div id="projectname">Doxygen
   </div>
  </td>
 </tr>
 </tbody>
</table>
</div>
<!-- end header part -->
<!-- 制作者 Doxygen 1.9.1 -->
<script type="text/javascript">
/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&amp;dn=gpl-2.0.txt GPL-v2 */
var searchBox = new SearchBox("searchBox", "search",false,'搜索','.html');
/* @license-end */
</script>
<script type="text/javascript" src="menudata.js"></script>
<script type="text/javascript" src="menu.js"></script>
<script type="text/javascript">
/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&amp;dn=gpl-2.0.txt GPL-v2 */
$(function() {
  initMenu('',true,false,'search.php','搜索');
  $(document).ready(function() { init_search(); });
});
/* @license-end */</script>
<div id="main-nav"></div>
</div><!-- top -->
<div id="side-nav" class="ui-resizable side-nav-resizable">
  <div id="nav-tree">
    <div id="nav-tree-contents">
      <div id="nav-sync" class="sync"></div>
    </div>
  </div>
  <div id="splitbar" style="-moz-user-select:none;" 
       class="ui-resizable-handle">
  </div>
</div>
<script type="text/javascript">
/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&amp;dn=gpl-2.0.txt GPL-v2 */
$(document).ready(function(){initNavTree('classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html',''); initResizable(); });
/* @license-end */
</script>
<div id="doc-content">
<!-- window showing the filter options -->
<div id="MSearchSelectWindow"
     onmouseover="return searchBox.OnSearchSelectShow()"
     onmouseout="return searchBox.OnSearchSelectHide()"
     onkeydown="return searchBox.OnSearchSelectKey(event)">
</div>

<!-- iframe showing the search results (closed by default) -->
<div id="MSearchResultsWindow">
<iframe src="javascript:void(0)" frameborder="0" 
        name="MSearchResults" id="MSearchResults">
</iframe>
</div>

<div class="header">
  <div class="summary">
<a href="#pub-types">Public 类型</a> &#124;
<a href="#pub-methods">Public 成员函数</a> &#124;
<a href="#pro-methods">Protected 成员函数</a> &#124;
<a href="#pri-attribs">Private 属性</a> &#124;
<a href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting-members.html">所有成员列表</a>  </div>
  <div class="headertitle">
<div class="title">pcl::registration::CorrespondenceEstimationNormalShooting&lt; PointSource, PointTarget, NormalT, Scalar &gt; 模板类 参考</div>  </div>
</div><!--header-->
<div class="contents">

<p><b><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html" title="CorrespondenceEstimationNormalShooting computes correspondences as points in the target cloud which h...">CorrespondenceEstimationNormalShooting</a></b> computes correspondences as points in the target cloud which have minimum distance to normals computed on the input cloud  
 <a href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#details">更多...</a></p>

<p><code>#include &lt;<a class="el" href="correspondence__estimation__normal__shooting_8h_source.html">correspondence_estimation_normal_shooting.h</a>&gt;</code></p>
<div class="dynheader">
类 pcl::registration::CorrespondenceEstimationNormalShooting&lt; PointSource, PointTarget, NormalT, Scalar &gt; 继承关系图:</div>
<div class="dyncontent">
 <div class="center">
  <img src="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.png" usemap="#pcl::registration::CorrespondenceEstimationNormalShooting_3C_20PointSource_2C_20PointTarget_2C_20NormalT_2C_20Scalar_20_3E_map" alt=""/>
  <map id="pcl::registration::CorrespondenceEstimationNormalShooting_3C_20PointSource_2C_20PointTarget_2C_20NormalT_2C_20Scalar_20_3E_map" name="pcl::registration::CorrespondenceEstimationNormalShooting_3C_20PointSource_2C_20PointTarget_2C_20NormalT_2C_20Scalar_20_3E_map">
<area href="classpcl_1_1registration_1_1_correspondence_estimation_base.html" alt="pcl::registration::CorrespondenceEstimationBase&lt; PointSource, PointTarget, float &gt;" shape="rect" coords="0,56,612,80"/>
<area href="classpcl_1_1_p_c_l_base.html" alt="pcl::PCLBase&lt; PointSource &gt;" shape="rect" coords="0,0,612,24"/>
  </map>
</div></div>
<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-types"></a>
Public 类型</h2></td></tr>
<tr class="memitem:a3002a9822e0151743b6768d82a4b7d87"><td class="memItemLeft" align="right" valign="top"><a id="a3002a9822e0151743b6768d82a4b7d87"></a>
typedef boost::shared_ptr&lt; <a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html">CorrespondenceEstimationNormalShooting</a>&lt; PointSource, PointTarget, <a class="el" href="structpcl_1_1_normal.html">NormalT</a>, Scalar &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>Ptr</b></td></tr>
<tr class="separator:a3002a9822e0151743b6768d82a4b7d87"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a671a5cd4b411e3b10d2c2352343e776b"><td class="memItemLeft" align="right" valign="top"><a id="a671a5cd4b411e3b10d2c2352343e776b"></a>
typedef boost::shared_ptr&lt; const <a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html">CorrespondenceEstimationNormalShooting</a>&lt; PointSource, PointTarget, <a class="el" href="structpcl_1_1_normal.html">NormalT</a>, Scalar &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>ConstPtr</b></td></tr>
<tr class="separator:a671a5cd4b411e3b10d2c2352343e776b"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac86685797d9a90baf28c1d9f8f29aa05"><td class="memItemLeft" align="right" valign="top"><a id="ac86685797d9a90baf28c1d9f8f29aa05"></a>
typedef <a class="el" href="classpcl_1_1search_1_1_kd_tree.html">pcl::search::KdTree</a>&lt; PointTarget &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>KdTree</b></td></tr>
<tr class="separator:ac86685797d9a90baf28c1d9f8f29aa05"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a09ac974603735fd9c9743eb746f9df2c"><td class="memItemLeft" align="right" valign="top"><a id="a09ac974603735fd9c9743eb746f9df2c"></a>
typedef <a class="el" href="classpcl_1_1search_1_1_kd_tree.html">pcl::search::KdTree</a>&lt; PointTarget &gt;::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>KdTreePtr</b></td></tr>
<tr class="separator:a09ac974603735fd9c9743eb746f9df2c"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae91318203c75d794e36156aad6a91917"><td class="memItemLeft" align="right" valign="top"><a id="ae91318203c75d794e36156aad6a91917"></a>
typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; PointSource &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudSource</b></td></tr>
<tr class="separator:ae91318203c75d794e36156aad6a91917"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2217d74ffafb2393c8f966d6a6c0ce8a"><td class="memItemLeft" align="right" valign="top"><a id="a2217d74ffafb2393c8f966d6a6c0ce8a"></a>
typedef PointCloudSource::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudSourcePtr</b></td></tr>
<tr class="separator:a2217d74ffafb2393c8f966d6a6c0ce8a"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aac1ee46e47ca56981f5d3554dc4276df"><td class="memItemLeft" align="right" valign="top"><a id="aac1ee46e47ca56981f5d3554dc4276df"></a>
typedef PointCloudSource::ConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudSourceConstPtr</b></td></tr>
<tr class="separator:aac1ee46e47ca56981f5d3554dc4276df"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a14ac0d7c87d8bb795f566fade144237f"><td class="memItemLeft" align="right" valign="top"><a id="a14ac0d7c87d8bb795f566fade144237f"></a>
typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; PointTarget &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudTarget</b></td></tr>
<tr class="separator:a14ac0d7c87d8bb795f566fade144237f"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a6b826c08f39faf45f45c398dfa19be87"><td class="memItemLeft" align="right" valign="top"><a id="a6b826c08f39faf45f45c398dfa19be87"></a>
typedef PointCloudTarget::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudTargetPtr</b></td></tr>
<tr class="separator:a6b826c08f39faf45f45c398dfa19be87"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a20046450936873be5165c1fda7b1d70e"><td class="memItemLeft" align="right" valign="top"><a id="a20046450936873be5165c1fda7b1d70e"></a>
typedef PointCloudTarget::ConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudTargetConstPtr</b></td></tr>
<tr class="separator:a20046450936873be5165c1fda7b1d70e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aed3e258c71ae1a64ac88e1ec441c28d8"><td class="memItemLeft" align="right" valign="top"><a id="aed3e258c71ae1a64ac88e1ec441c28d8"></a>
typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_normal.html">NormalT</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudNormals</b></td></tr>
<tr class="separator:aed3e258c71ae1a64ac88e1ec441c28d8"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:adeabd5595d4127cb88dde4732010e929"><td class="memItemLeft" align="right" valign="top"><a id="adeabd5595d4127cb88dde4732010e929"></a>
typedef PointCloudNormals::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>NormalsPtr</b></td></tr>
<tr class="separator:adeabd5595d4127cb88dde4732010e929"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:afa51b3667a1cb4dfa8b67bfc490ffab7"><td class="memItemLeft" align="right" valign="top"><a id="afa51b3667a1cb4dfa8b67bfc490ffab7"></a>
typedef PointCloudNormals::ConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>NormalsConstPtr</b></td></tr>
<tr class="separator:afa51b3667a1cb4dfa8b67bfc490ffab7"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td colspan="2" onclick="javascript:toggleInherit('pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base')"><img src="closed.png" alt="-"/>&#160;Public 类型 继承自 <a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html">pcl::registration::CorrespondenceEstimationBase&lt; PointSource, PointTarget, float &gt;</a></td></tr>
<tr class="memitem:abc26658ace3b34d14e808599b6b6ad17 inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="abc26658ace3b34d14e808599b6b6ad17"></a>
typedef boost::shared_ptr&lt; <a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html">CorrespondenceEstimationBase</a>&lt; PointSource, PointTarget, float &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>Ptr</b></td></tr>
<tr class="separator:abc26658ace3b34d14e808599b6b6ad17 inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac08e02da4643d7120c8e382b6baf7799 inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="ac08e02da4643d7120c8e382b6baf7799"></a>
typedef boost::shared_ptr&lt; const <a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html">CorrespondenceEstimationBase</a>&lt; PointSource, PointTarget, float &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>ConstPtr</b></td></tr>
<tr class="separator:ac08e02da4643d7120c8e382b6baf7799 inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a43ef5e39ae51e4d65677575c66e15a7f inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="a43ef5e39ae51e4d65677575c66e15a7f"></a>
typedef <a class="el" href="classpcl_1_1search_1_1_kd_tree.html">pcl::search::KdTree</a>&lt; PointTarget &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>KdTree</b></td></tr>
<tr class="separator:a43ef5e39ae51e4d65677575c66e15a7f inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af57574187cba57fdf480cb51e7a97cf2 inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="af57574187cba57fdf480cb51e7a97cf2"></a>
typedef KdTree::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>KdTreePtr</b></td></tr>
<tr class="separator:af57574187cba57fdf480cb51e7a97cf2 inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a8a6a7af63f47bc195b0028e11bda4b98 inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="a8a6a7af63f47bc195b0028e11bda4b98"></a>
typedef <a class="el" href="classpcl_1_1search_1_1_kd_tree.html">pcl::search::KdTree</a>&lt; PointSource &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>KdTreeReciprocal</b></td></tr>
<tr class="separator:a8a6a7af63f47bc195b0028e11bda4b98 inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af1d23dfb1e222c7a7bce2358ab7357db inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="af1d23dfb1e222c7a7bce2358ab7357db"></a>
typedef KdTree::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>KdTreeReciprocalPtr</b></td></tr>
<tr class="separator:af1d23dfb1e222c7a7bce2358ab7357db inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aee35a52b4a4893fb841293814a227673 inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="aee35a52b4a4893fb841293814a227673"></a>
typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; PointSource &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudSource</b></td></tr>
<tr class="separator:aee35a52b4a4893fb841293814a227673 inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a4effa970b306701c52d6797e574ecd21 inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="a4effa970b306701c52d6797e574ecd21"></a>
typedef PointCloudSource::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudSourcePtr</b></td></tr>
<tr class="separator:a4effa970b306701c52d6797e574ecd21 inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a0918d5b78e72ecf10dd5151547dbea7e inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="a0918d5b78e72ecf10dd5151547dbea7e"></a>
typedef PointCloudSource::ConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudSourceConstPtr</b></td></tr>
<tr class="separator:a0918d5b78e72ecf10dd5151547dbea7e inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a71e44d7dfe22e45214b9fad6e7a2d438 inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="a71e44d7dfe22e45214b9fad6e7a2d438"></a>
typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; PointTarget &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudTarget</b></td></tr>
<tr class="separator:a71e44d7dfe22e45214b9fad6e7a2d438 inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae496eb0b1a9ac7eb0844fdf45b60f729 inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="ae496eb0b1a9ac7eb0844fdf45b60f729"></a>
typedef PointCloudTarget::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudTargetPtr</b></td></tr>
<tr class="separator:ae496eb0b1a9ac7eb0844fdf45b60f729 inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a6de153ae1cca2452342fceb204118d49 inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="a6de153ae1cca2452342fceb204118d49"></a>
typedef PointCloudTarget::ConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudTargetConstPtr</b></td></tr>
<tr class="separator:a6de153ae1cca2452342fceb204118d49 inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae6c14122c36e11642c21b71197ef56ba inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="ae6c14122c36e11642c21b71197ef56ba"></a>
typedef KdTree::PointRepresentationConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointRepresentationConstPtr</b></td></tr>
<tr class="separator:ae6c14122c36e11642c21b71197ef56ba inherit pub_types_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pub_types_classpcl_1_1_p_c_l_base"><td colspan="2" onclick="javascript:toggleInherit('pub_types_classpcl_1_1_p_c_l_base')"><img src="closed.png" alt="-"/>&#160;Public 类型 继承自 <a class="el" href="classpcl_1_1_p_c_l_base.html">pcl::PCLBase&lt; PointSource &gt;</a></td></tr>
<tr class="memitem:ae2f6f6863a73337858b7a7a054eaae4f inherit pub_types_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="ae2f6f6863a73337858b7a7a054eaae4f"></a>
typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; PointSource &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloud</b></td></tr>
<tr class="separator:ae2f6f6863a73337858b7a7a054eaae4f inherit pub_types_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab84dd662cda89edb882fe5307b2136ea inherit pub_types_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="ab84dd662cda89edb882fe5307b2136ea"></a>
typedef PointCloud::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudPtr</b></td></tr>
<tr class="separator:ab84dd662cda89edb882fe5307b2136ea inherit pub_types_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac8326513fad0680b6993e2f1a79a6af4 inherit pub_types_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="ac8326513fad0680b6993e2f1a79a6af4"></a>
typedef PointCloud::ConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudConstPtr</b></td></tr>
<tr class="separator:ac8326513fad0680b6993e2f1a79a6af4 inherit pub_types_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae51eae0c7b3e0b7178f4894dff90660a inherit pub_types_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="ae51eae0c7b3e0b7178f4894dff90660a"></a>
typedef boost::shared_ptr&lt; <a class="el" href="structpcl_1_1_point_indices.html">PointIndices</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointIndicesPtr</b></td></tr>
<tr class="separator:ae51eae0c7b3e0b7178f4894dff90660a inherit pub_types_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a51771056fb4ab8c448a11157acbe2ee0 inherit pub_types_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="a51771056fb4ab8c448a11157acbe2ee0"></a>
typedef boost::shared_ptr&lt; <a class="el" href="structpcl_1_1_point_indices.html">PointIndices</a> const &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointIndicesConstPtr</b></td></tr>
<tr class="separator:a51771056fb4ab8c448a11157acbe2ee0 inherit pub_types_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public 成员函数</h2></td></tr>
<tr class="memitem:aae2aa6649dac6840562cf392d6c8fe8c"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#aae2aa6649dac6840562cf392d6c8fe8c">CorrespondenceEstimationNormalShooting</a> ()</td></tr>
<tr class="memdesc:aae2aa6649dac6840562cf392d6c8fe8c"><td class="mdescLeft">&#160;</td><td class="mdescRight">Empty constructor.  <a href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#aae2aa6649dac6840562cf392d6c8fe8c">更多...</a><br /></td></tr>
<tr class="separator:aae2aa6649dac6840562cf392d6c8fe8c"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af6c28e356be7e759e4f790405855f326"><td class="memItemLeft" align="right" valign="top"><a id="af6c28e356be7e759e4f790405855f326"></a>
virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#af6c28e356be7e759e4f790405855f326">~CorrespondenceEstimationNormalShooting</a> ()</td></tr>
<tr class="memdesc:af6c28e356be7e759e4f790405855f326"><td class="mdescLeft">&#160;</td><td class="mdescRight">Empty destructor <br /></td></tr>
<tr class="separator:af6c28e356be7e759e4f790405855f326"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af651fe7489cf7cab8eb622e1d77f642e"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#af651fe7489cf7cab8eb622e1d77f642e">setSourceNormals</a> (const NormalsConstPtr &amp;normals)</td></tr>
<tr class="memdesc:af651fe7489cf7cab8eb622e1d77f642e"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the normals computed on the source point cloud  <a href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#af651fe7489cf7cab8eb622e1d77f642e">更多...</a><br /></td></tr>
<tr class="separator:af651fe7489cf7cab8eb622e1d77f642e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae38f83809f3a4739b44098727a58eeba"><td class="memItemLeft" align="right" valign="top"><a id="ae38f83809f3a4739b44098727a58eeba"></a>
NormalsConstPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#ae38f83809f3a4739b44098727a58eeba">getSourceNormals</a> () const</td></tr>
<tr class="memdesc:ae38f83809f3a4739b44098727a58eeba"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the normals of the source point cloud <br /></td></tr>
<tr class="separator:ae38f83809f3a4739b44098727a58eeba"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a72059662927cecbee745994cf11f8f95"><td class="memItemLeft" align="right" valign="top"><a id="a72059662927cecbee745994cf11f8f95"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a72059662927cecbee745994cf11f8f95">requiresSourceNormals</a> () const</td></tr>
<tr class="memdesc:a72059662927cecbee745994cf11f8f95"><td class="mdescLeft">&#160;</td><td class="mdescRight">See if this rejector requires source normals <br /></td></tr>
<tr class="separator:a72059662927cecbee745994cf11f8f95"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3c58891ab3b0bfd318c5a732adc3cd60"><td class="memItemLeft" align="right" valign="top"><a id="a3c58891ab3b0bfd318c5a732adc3cd60"></a>
void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a3c58891ab3b0bfd318c5a732adc3cd60">setSourceNormals</a> (pcl::PCLPointCloud2::ConstPtr cloud2)</td></tr>
<tr class="memdesc:a3c58891ab3b0bfd318c5a732adc3cd60"><td class="mdescLeft">&#160;</td><td class="mdescRight">Blob method for setting the source normals <br /></td></tr>
<tr class="separator:a3c58891ab3b0bfd318c5a732adc3cd60"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a348a50a8b8a0d3c5b14704d283ce068c"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a348a50a8b8a0d3c5b14704d283ce068c">determineCorrespondences</a> (pcl::Correspondences &amp;correspondences, double max_distance=std::numeric_limits&lt; double &gt;::max())</td></tr>
<tr class="memdesc:a348a50a8b8a0d3c5b14704d283ce068c"><td class="mdescLeft">&#160;</td><td class="mdescRight">Determine the correspondences between input and target cloud.  <a href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a348a50a8b8a0d3c5b14704d283ce068c">更多...</a><br /></td></tr>
<tr class="separator:a348a50a8b8a0d3c5b14704d283ce068c"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a93c946684ceff4a5686852be95852835"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a93c946684ceff4a5686852be95852835">determineReciprocalCorrespondences</a> (pcl::Correspondences &amp;correspondences, double max_distance=std::numeric_limits&lt; double &gt;::max())</td></tr>
<tr class="memdesc:a93c946684ceff4a5686852be95852835"><td class="mdescLeft">&#160;</td><td class="mdescRight">Determine the reciprocal correspondences between input and target cloud. A correspondence is considered reciprocal if both Src_i has Tgt_i as a correspondence, and Tgt_i has Src_i as one.  <a href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a93c946684ceff4a5686852be95852835">更多...</a><br /></td></tr>
<tr class="separator:a93c946684ceff4a5686852be95852835"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a6a9dba31ba0d0be3a2befe13a56a5f5a"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a6a9dba31ba0d0be3a2befe13a56a5f5a">setKSearch</a> (unsigned int k)</td></tr>
<tr class="memdesc:a6a9dba31ba0d0be3a2befe13a56a5f5a"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the number of nearest neighbours to be considered in the target point cloud. By default, we use k = 10 nearest neighbors.  <a href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a6a9dba31ba0d0be3a2befe13a56a5f5a">更多...</a><br /></td></tr>
<tr class="separator:a6a9dba31ba0d0be3a2befe13a56a5f5a"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a624e74883b42919e9ced84c360d21d1f"><td class="memItemLeft" align="right" valign="top"><a id="a624e74883b42919e9ced84c360d21d1f"></a>
unsigned int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a624e74883b42919e9ced84c360d21d1f">getKSearch</a> () const</td></tr>
<tr class="memdesc:a624e74883b42919e9ced84c360d21d1f"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the number of nearest neighbours considered in the target point cloud for computing correspondences. By default we use k = 10 nearest neighbors. <br /></td></tr>
<tr class="separator:a624e74883b42919e9ced84c360d21d1f"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a5abc2caed920d36cbf23e027d5294227"><td class="memItemLeft" align="right" valign="top"><a id="a5abc2caed920d36cbf23e027d5294227"></a>
virtual boost::shared_ptr&lt; <a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html">CorrespondenceEstimationBase</a>&lt; PointSource, PointTarget, Scalar &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a5abc2caed920d36cbf23e027d5294227">clone</a> () const</td></tr>
<tr class="memdesc:a5abc2caed920d36cbf23e027d5294227"><td class="mdescLeft">&#160;</td><td class="mdescRight">Clone and cast to <a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html" title="Abstract CorrespondenceEstimationBase class. All correspondence estimation methods should inherit fro...">CorrespondenceEstimationBase</a> <br /></td></tr>
<tr class="separator:a5abc2caed920d36cbf23e027d5294227"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base')"><img src="closed.png" alt="-"/>&#160;Public 成员函数 继承自 <a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html">pcl::registration::CorrespondenceEstimationBase&lt; PointSource, PointTarget, float &gt;</a></td></tr>
<tr class="memitem:a44d06d7569b9d4e0115e741ce495b622 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="a44d06d7569b9d4e0115e741ce495b622"></a>
&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a44d06d7569b9d4e0115e741ce495b622">CorrespondenceEstimationBase</a> ()</td></tr>
<tr class="memdesc:a44d06d7569b9d4e0115e741ce495b622 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Empty constructor. <br /></td></tr>
<tr class="separator:a44d06d7569b9d4e0115e741ce495b622 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a16a1c24a3cf934cfb23920c425a6ff88 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="a16a1c24a3cf934cfb23920c425a6ff88"></a>
virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a16a1c24a3cf934cfb23920c425a6ff88">~CorrespondenceEstimationBase</a> ()</td></tr>
<tr class="memdesc:a16a1c24a3cf934cfb23920c425a6ff88 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Empty destructor <br /></td></tr>
<tr class="separator:a16a1c24a3cf934cfb23920c425a6ff88 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a5b6f6dcae4eeee851931cb37c98b64d7 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a5b6f6dcae4eeee851931cb37c98b64d7">setInputCloud</a> (const PointCloudSourceConstPtr &amp;cloud)</td></tr>
<tr class="memdesc:a5b6f6dcae4eeee851931cb37c98b64d7 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the input source (e.g., the point cloud that we want to align to the target)  <a href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a5b6f6dcae4eeee851931cb37c98b64d7">更多...</a><br /></td></tr>
<tr class="separator:a5b6f6dcae4eeee851931cb37c98b64d7 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a11120b8b747b53613e8bc2276e7cdcb3 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="a11120b8b747b53613e8bc2276e7cdcb3"></a>
PointCloudSourceConstPtr const&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a11120b8b747b53613e8bc2276e7cdcb3">getInputCloud</a> ()</td></tr>
<tr class="memdesc:a11120b8b747b53613e8bc2276e7cdcb3 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the input point cloud dataset target. <br /></td></tr>
<tr class="separator:a11120b8b747b53613e8bc2276e7cdcb3 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa67db523c5d262b6ca1782847e27c563 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#aa67db523c5d262b6ca1782847e27c563">setInputSource</a> (const PointCloudSourceConstPtr &amp;cloud)</td></tr>
<tr class="memdesc:aa67db523c5d262b6ca1782847e27c563 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the input source (e.g., the point cloud that we want to align to the target)  <a href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#aa67db523c5d262b6ca1782847e27c563">更多...</a><br /></td></tr>
<tr class="separator:aa67db523c5d262b6ca1782847e27c563 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:acbc245bbab3b1fb9c80f736e8134cd4a inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="acbc245bbab3b1fb9c80f736e8134cd4a"></a>
PointCloudSourceConstPtr const&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#acbc245bbab3b1fb9c80f736e8134cd4a">getInputSource</a> ()</td></tr>
<tr class="memdesc:acbc245bbab3b1fb9c80f736e8134cd4a inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the input point cloud dataset target. <br /></td></tr>
<tr class="separator:acbc245bbab3b1fb9c80f736e8134cd4a inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:abb8906b3ab5948cc3b58bf7b22218eea inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#abb8906b3ab5948cc3b58bf7b22218eea">setInputTarget</a> (const PointCloudTargetConstPtr &amp;cloud)</td></tr>
<tr class="memdesc:abb8906b3ab5948cc3b58bf7b22218eea inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the input target (e.g., the point cloud that we want to align the input source to)  <a href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#abb8906b3ab5948cc3b58bf7b22218eea">更多...</a><br /></td></tr>
<tr class="separator:abb8906b3ab5948cc3b58bf7b22218eea inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a26f808434799242e8711a7c9355f3060 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="a26f808434799242e8711a7c9355f3060"></a>
PointCloudTargetConstPtr const&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a26f808434799242e8711a7c9355f3060">getInputTarget</a> ()</td></tr>
<tr class="memdesc:a26f808434799242e8711a7c9355f3060 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the input point cloud dataset target. <br /></td></tr>
<tr class="separator:a26f808434799242e8711a7c9355f3060 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aad23d9593864dde9da9fb52055c78604 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="aad23d9593864dde9da9fb52055c78604"></a>
virtual bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#aad23d9593864dde9da9fb52055c78604">requiresTargetNormals</a> () const</td></tr>
<tr class="memdesc:aad23d9593864dde9da9fb52055c78604 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">See if this rejector requires target normals <br /></td></tr>
<tr class="separator:aad23d9593864dde9da9fb52055c78604 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad189ec0c3db30c64ce24d3a8ca64527d inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="ad189ec0c3db30c64ce24d3a8ca64527d"></a>
virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#ad189ec0c3db30c64ce24d3a8ca64527d">setTargetNormals</a> (pcl::PCLPointCloud2::ConstPtr)</td></tr>
<tr class="memdesc:ad189ec0c3db30c64ce24d3a8ca64527d inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Abstract method for setting the target normals <br /></td></tr>
<tr class="separator:ad189ec0c3db30c64ce24d3a8ca64527d inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac2caef76d13492efb77731d318a251db inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#ac2caef76d13492efb77731d318a251db">setIndicesSource</a> (const IndicesPtr &amp;indices)</td></tr>
<tr class="memdesc:ac2caef76d13492efb77731d318a251db inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the vector of indices that represent the input source point cloud.  <a href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#ac2caef76d13492efb77731d318a251db">更多...</a><br /></td></tr>
<tr class="separator:ac2caef76d13492efb77731d318a251db inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa1cfa7439f71c3afe482dec5cd431b62 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="aa1cfa7439f71c3afe482dec5cd431b62"></a>
IndicesPtr const&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#aa1cfa7439f71c3afe482dec5cd431b62">getIndicesSource</a> ()</td></tr>
<tr class="memdesc:aa1cfa7439f71c3afe482dec5cd431b62 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the vector of indices used for the source dataset. <br /></td></tr>
<tr class="separator:aa1cfa7439f71c3afe482dec5cd431b62 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:addc63787ae74feaa7445442c9b108d95 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#addc63787ae74feaa7445442c9b108d95">setIndicesTarget</a> (const IndicesPtr &amp;indices)</td></tr>
<tr class="memdesc:addc63787ae74feaa7445442c9b108d95 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the vector of indices that represent the input target point cloud.  <a href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#addc63787ae74feaa7445442c9b108d95">更多...</a><br /></td></tr>
<tr class="separator:addc63787ae74feaa7445442c9b108d95 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a42e70967a7cb4f95e7d46d2d32ad0f30 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="a42e70967a7cb4f95e7d46d2d32ad0f30"></a>
IndicesPtr const&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a42e70967a7cb4f95e7d46d2d32ad0f30">getIndicesTarget</a> ()</td></tr>
<tr class="memdesc:a42e70967a7cb4f95e7d46d2d32ad0f30 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the vector of indices used for the target dataset. <br /></td></tr>
<tr class="separator:a42e70967a7cb4f95e7d46d2d32ad0f30 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a53aebf3a2649c712fcd1a0a0768ed51a inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a53aebf3a2649c712fcd1a0a0768ed51a">setSearchMethodTarget</a> (const KdTreePtr &amp;tree, bool force_no_recompute=false)</td></tr>
<tr class="memdesc:a53aebf3a2649c712fcd1a0a0768ed51a inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the search object used to find correspondences in the target cloud.  <a href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a53aebf3a2649c712fcd1a0a0768ed51a">更多...</a><br /></td></tr>
<tr class="separator:a53aebf3a2649c712fcd1a0a0768ed51a inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:afdb07975992d25faa783ecacd0adb71b inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="afdb07975992d25faa783ecacd0adb71b"></a>
KdTreePtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#afdb07975992d25faa783ecacd0adb71b">getSearchMethodTarget</a> () const</td></tr>
<tr class="memdesc:afdb07975992d25faa783ecacd0adb71b inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the search method used to find correspondences in the target cloud. <br /></td></tr>
<tr class="separator:afdb07975992d25faa783ecacd0adb71b inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a260ce83db343ffc513c779e87e18bb8a inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a260ce83db343ffc513c779e87e18bb8a">setSearchMethodSource</a> (const KdTreeReciprocalPtr &amp;tree, bool force_no_recompute=false)</td></tr>
<tr class="memdesc:a260ce83db343ffc513c779e87e18bb8a inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the search object used to find correspondences in the source cloud (usually used by reciprocal correspondence finding).  <a href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a260ce83db343ffc513c779e87e18bb8a">更多...</a><br /></td></tr>
<tr class="separator:a260ce83db343ffc513c779e87e18bb8a inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a890dbded17485123c0fa202aeeea01d5 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="a890dbded17485123c0fa202aeeea01d5"></a>
KdTreeReciprocalPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a890dbded17485123c0fa202aeeea01d5">getSearchMethodSource</a> () const</td></tr>
<tr class="memdesc:a890dbded17485123c0fa202aeeea01d5 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the search method used to find correspondences in the source cloud. <br /></td></tr>
<tr class="separator:a890dbded17485123c0fa202aeeea01d5 inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a45f38520f0b144dc85423f1395f043ab inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a45f38520f0b144dc85423f1395f043ab">setPointRepresentation</a> (const PointRepresentationConstPtr &amp;point_representation)</td></tr>
<tr class="memdesc:a45f38520f0b144dc85423f1395f043ab inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a boost shared pointer to the PointRepresentation to be used when searching for nearest neighbors.  <a href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a45f38520f0b144dc85423f1395f043ab">更多...</a><br /></td></tr>
<tr class="separator:a45f38520f0b144dc85423f1395f043ab inherit pub_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pub_methods_classpcl_1_1_p_c_l_base"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classpcl_1_1_p_c_l_base')"><img src="closed.png" alt="-"/>&#160;Public 成员函数 继承自 <a class="el" href="classpcl_1_1_p_c_l_base.html">pcl::PCLBase&lt; PointSource &gt;</a></td></tr>
<tr class="memitem:af4fbc5eb005057f8a0fc6d60bde595df inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="af4fbc5eb005057f8a0fc6d60bde595df"></a>
&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#af4fbc5eb005057f8a0fc6d60bde595df">PCLBase</a> ()</td></tr>
<tr class="memdesc:af4fbc5eb005057f8a0fc6d60bde595df inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Empty constructor. <br /></td></tr>
<tr class="separator:af4fbc5eb005057f8a0fc6d60bde595df inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7a6dd7a91275d7737cf1b18005b47244 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="a7a6dd7a91275d7737cf1b18005b47244"></a>
&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#a7a6dd7a91275d7737cf1b18005b47244">PCLBase</a> (const <a class="el" href="classpcl_1_1_p_c_l_base.html">PCLBase</a> &amp;base)</td></tr>
<tr class="memdesc:a7a6dd7a91275d7737cf1b18005b47244 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Copy constructor. <br /></td></tr>
<tr class="separator:a7a6dd7a91275d7737cf1b18005b47244 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad5d6846e98e59c37dcc3dc9958d53966 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="ad5d6846e98e59c37dcc3dc9958d53966"></a>
virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#ad5d6846e98e59c37dcc3dc9958d53966">~PCLBase</a> ()</td></tr>
<tr class="memdesc:ad5d6846e98e59c37dcc3dc9958d53966 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Destructor. <br /></td></tr>
<tr class="separator:ad5d6846e98e59c37dcc3dc9958d53966 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a8cd745c4f7a792212f4fc3720b9d46ea inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="a8cd745c4f7a792212f4fc3720b9d46ea"></a>
PointCloudConstPtr const&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#a8cd745c4f7a792212f4fc3720b9d46ea">getInputCloud</a> () const</td></tr>
<tr class="memdesc:a8cd745c4f7a792212f4fc3720b9d46ea inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the input point cloud dataset. <br /></td></tr>
<tr class="separator:a8cd745c4f7a792212f4fc3720b9d46ea inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab219359de6eb34c9d51e2e976dd1a0d1 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#ab219359de6eb34c9d51e2e976dd1a0d1">setIndices</a> (const IndicesPtr &amp;indices)</td></tr>
<tr class="memdesc:ab219359de6eb34c9d51e2e976dd1a0d1 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the vector of indices that represents the input data.  <a href="classpcl_1_1_p_c_l_base.html#ab219359de6eb34c9d51e2e976dd1a0d1">更多...</a><br /></td></tr>
<tr class="separator:ab219359de6eb34c9d51e2e976dd1a0d1 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a436c68c74b31e4dd00000adfbb11ca7c inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#a436c68c74b31e4dd00000adfbb11ca7c">setIndices</a> (const IndicesConstPtr &amp;indices)</td></tr>
<tr class="memdesc:a436c68c74b31e4dd00000adfbb11ca7c inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the vector of indices that represents the input data.  <a href="classpcl_1_1_p_c_l_base.html#a436c68c74b31e4dd00000adfbb11ca7c">更多...</a><br /></td></tr>
<tr class="separator:a436c68c74b31e4dd00000adfbb11ca7c inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af9cc90d8364ce968566f75800d3773ca inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#af9cc90d8364ce968566f75800d3773ca">setIndices</a> (const PointIndicesConstPtr &amp;indices)</td></tr>
<tr class="memdesc:af9cc90d8364ce968566f75800d3773ca inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the vector of indices that represents the input data.  <a href="classpcl_1_1_p_c_l_base.html#af9cc90d8364ce968566f75800d3773ca">更多...</a><br /></td></tr>
<tr class="separator:af9cc90d8364ce968566f75800d3773ca inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a930c7a6375fdf65ff8cfdb4eb4a6d996 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#a930c7a6375fdf65ff8cfdb4eb4a6d996">setIndices</a> (size_t row_start, size_t col_start, size_t nb_rows, size_t nb_cols)</td></tr>
<tr class="memdesc:a930c7a6375fdf65ff8cfdb4eb4a6d996 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the indices for the points laying within an interest region of the point cloud.  <a href="classpcl_1_1_p_c_l_base.html#a930c7a6375fdf65ff8cfdb4eb4a6d996">更多...</a><br /></td></tr>
<tr class="separator:a930c7a6375fdf65ff8cfdb4eb4a6d996 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a058753dd4de73d3d0062fe2e452fba3c inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="a058753dd4de73d3d0062fe2e452fba3c"></a>
IndicesPtr const&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#a058753dd4de73d3d0062fe2e452fba3c">getIndices</a> ()</td></tr>
<tr class="memdesc:a058753dd4de73d3d0062fe2e452fba3c inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the vector of indices used. <br /></td></tr>
<tr class="separator:a058753dd4de73d3d0062fe2e452fba3c inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:acae187b37230758959572ceb1e6e2045 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="acae187b37230758959572ceb1e6e2045"></a>
IndicesConstPtr const&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#acae187b37230758959572ceb1e6e2045">getIndices</a> () const</td></tr>
<tr class="memdesc:acae187b37230758959572ceb1e6e2045 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the vector of indices used. <br /></td></tr>
<tr class="separator:acae187b37230758959572ceb1e6e2045 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af7335fedb0af0930b9d1dedcb54ba201 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top">const PointSource &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#af7335fedb0af0930b9d1dedcb54ba201">operator[]</a> (size_t pos) const</td></tr>
<tr class="memdesc:af7335fedb0af0930b9d1dedcb54ba201 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Override PointCloud operator[] to shorten code  <a href="classpcl_1_1_p_c_l_base.html#af7335fedb0af0930b9d1dedcb54ba201">更多...</a><br /></td></tr>
<tr class="separator:af7335fedb0af0930b9d1dedcb54ba201 inherit pub_methods_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pro-methods"></a>
Protected 成员函数</h2></td></tr>
<tr class="memitem:af979935c7f43038ab68ad6d0d701a801"><td class="memItemLeft" align="right" valign="top"><a id="af979935c7f43038ab68ad6d0d701a801"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#af979935c7f43038ab68ad6d0d701a801">initCompute</a> ()</td></tr>
<tr class="memdesc:af979935c7f43038ab68ad6d0d701a801"><td class="mdescLeft">&#160;</td><td class="mdescRight">Internal computation initalization. <br /></td></tr>
<tr class="separator:af979935c7f43038ab68ad6d0d701a801"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pro_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td colspan="2" onclick="javascript:toggleInherit('pro_methods_classpcl_1_1registration_1_1_correspondence_estimation_base')"><img src="closed.png" alt="-"/>&#160;Protected 成员函数 继承自 <a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html">pcl::registration::CorrespondenceEstimationBase&lt; PointSource, PointTarget, float &gt;</a></td></tr>
<tr class="memitem:a4563c3bc0cb5d0270457d09ee9bdd03d inherit pro_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="a4563c3bc0cb5d0270457d09ee9bdd03d"></a>
const std::string &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a4563c3bc0cb5d0270457d09ee9bdd03d">getClassName</a> () const</td></tr>
<tr class="memdesc:a4563c3bc0cb5d0270457d09ee9bdd03d inherit pro_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Abstract class get name method. <br /></td></tr>
<tr class="separator:a4563c3bc0cb5d0270457d09ee9bdd03d inherit pro_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a38466f5d8f817f1fc9e62dfffff572c7 inherit pro_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="a38466f5d8f817f1fc9e62dfffff572c7"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a38466f5d8f817f1fc9e62dfffff572c7">initCompute</a> ()</td></tr>
<tr class="memdesc:a38466f5d8f817f1fc9e62dfffff572c7 inherit pro_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Internal computation initalization. <br /></td></tr>
<tr class="separator:a38466f5d8f817f1fc9e62dfffff572c7 inherit pro_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad7afb551d656990f5caf03ba2fc5f6c0 inherit pro_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="ad7afb551d656990f5caf03ba2fc5f6c0"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#ad7afb551d656990f5caf03ba2fc5f6c0">initComputeReciprocal</a> ()</td></tr>
<tr class="memdesc:ad7afb551d656990f5caf03ba2fc5f6c0 inherit pro_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Internal computation initalization for reciprocal correspondences. <br /></td></tr>
<tr class="separator:ad7afb551d656990f5caf03ba2fc5f6c0 inherit pro_methods_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pro_methods_classpcl_1_1_p_c_l_base"><td colspan="2" onclick="javascript:toggleInherit('pro_methods_classpcl_1_1_p_c_l_base')"><img src="closed.png" alt="-"/>&#160;Protected 成员函数 继承自 <a class="el" href="classpcl_1_1_p_c_l_base.html">pcl::PCLBase&lt; PointSource &gt;</a></td></tr>
<tr class="memitem:acceb20854934f4cf77e266eb5a44d4f0 inherit pro_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#acceb20854934f4cf77e266eb5a44d4f0">initCompute</a> ()</td></tr>
<tr class="memdesc:acceb20854934f4cf77e266eb5a44d4f0 inherit pro_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">This method should get called before starting the actual computation.  <a href="classpcl_1_1_p_c_l_base.html#acceb20854934f4cf77e266eb5a44d4f0">更多...</a><br /></td></tr>
<tr class="separator:acceb20854934f4cf77e266eb5a44d4f0 inherit pro_methods_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:afc426c4eebb94b7734d4fa556bff1420 inherit pro_methods_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="afc426c4eebb94b7734d4fa556bff1420"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#afc426c4eebb94b7734d4fa556bff1420">deinitCompute</a> ()</td></tr>
<tr class="memdesc:afc426c4eebb94b7734d4fa556bff1420 inherit pro_methods_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">This method should get called after finishing the actual computation. <br /></td></tr>
<tr class="separator:afc426c4eebb94b7734d4fa556bff1420 inherit pro_methods_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pri-attribs"></a>
Private 属性</h2></td></tr>
<tr class="memitem:a2ee2f0004f3cfd8463689c7c5f2cd5d6"><td class="memItemLeft" align="right" valign="top"><a id="a2ee2f0004f3cfd8463689c7c5f2cd5d6"></a>
NormalsConstPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a2ee2f0004f3cfd8463689c7c5f2cd5d6">source_normals_</a></td></tr>
<tr class="memdesc:a2ee2f0004f3cfd8463689c7c5f2cd5d6"><td class="mdescLeft">&#160;</td><td class="mdescRight">The normals computed at each point in the source cloud <br /></td></tr>
<tr class="separator:a2ee2f0004f3cfd8463689c7c5f2cd5d6"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a970b25748b2d88d9683594322b11e6de"><td class="memItemLeft" align="right" valign="top"><a id="a970b25748b2d88d9683594322b11e6de"></a>
NormalsPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a970b25748b2d88d9683594322b11e6de">source_normals_transformed_</a></td></tr>
<tr class="memdesc:a970b25748b2d88d9683594322b11e6de"><td class="mdescLeft">&#160;</td><td class="mdescRight">The normals computed at each point in the source cloud <br /></td></tr>
<tr class="separator:a970b25748b2d88d9683594322b11e6de"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a851e08a9f9c179228a59e39323bb9ca1"><td class="memItemLeft" align="right" valign="top"><a id="a851e08a9f9c179228a59e39323bb9ca1"></a>
unsigned int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a851e08a9f9c179228a59e39323bb9ca1">k_</a></td></tr>
<tr class="memdesc:a851e08a9f9c179228a59e39323bb9ca1"><td class="mdescLeft">&#160;</td><td class="mdescRight">The number of neighbours to be considered in the target point cloud <br /></td></tr>
<tr class="separator:a851e08a9f9c179228a59e39323bb9ca1"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="inherited"></a>
额外继承的成员函数</h2></td></tr>
<tr class="inherit_header pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td colspan="2" onclick="javascript:toggleInherit('pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base')"><img src="closed.png" alt="-"/>&#160;Protected 属性 继承自 <a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html">pcl::registration::CorrespondenceEstimationBase&lt; PointSource, PointTarget, float &gt;</a></td></tr>
<tr class="memitem:abafd815fa41e4762057c1351fa58c552 inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="abafd815fa41e4762057c1351fa58c552"></a>
std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#abafd815fa41e4762057c1351fa58c552">corr_name_</a></td></tr>
<tr class="memdesc:abafd815fa41e4762057c1351fa58c552 inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">The correspondence estimation method name. <br /></td></tr>
<tr class="separator:abafd815fa41e4762057c1351fa58c552 inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac43aa82c5e2d08b017639cc483d88ea2 inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="ac43aa82c5e2d08b017639cc483d88ea2"></a>
KdTreePtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#ac43aa82c5e2d08b017639cc483d88ea2">tree_</a></td></tr>
<tr class="memdesc:ac43aa82c5e2d08b017639cc483d88ea2 inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">A pointer to the spatial search object used for the target dataset. <br /></td></tr>
<tr class="separator:ac43aa82c5e2d08b017639cc483d88ea2 inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad15e1f9630bc3bb5e5c412dc8e9183ff inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="ad15e1f9630bc3bb5e5c412dc8e9183ff"></a>
KdTreeReciprocalPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#ad15e1f9630bc3bb5e5c412dc8e9183ff">tree_reciprocal_</a></td></tr>
<tr class="memdesc:ad15e1f9630bc3bb5e5c412dc8e9183ff inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">A pointer to the spatial search object used for the source dataset. <br /></td></tr>
<tr class="separator:ad15e1f9630bc3bb5e5c412dc8e9183ff inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a269bd2ef4d241dc4dafebe6919e5650e inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="a269bd2ef4d241dc4dafebe6919e5650e"></a>
PointCloudTargetConstPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a269bd2ef4d241dc4dafebe6919e5650e">target_</a></td></tr>
<tr class="memdesc:a269bd2ef4d241dc4dafebe6919e5650e inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">The input point cloud dataset target. <br /></td></tr>
<tr class="separator:a269bd2ef4d241dc4dafebe6919e5650e inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:adb7ffc631b61dd54251b907d9b59c36b inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="adb7ffc631b61dd54251b907d9b59c36b"></a>
IndicesPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#adb7ffc631b61dd54251b907d9b59c36b">target_indices_</a></td></tr>
<tr class="memdesc:adb7ffc631b61dd54251b907d9b59c36b inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">The target point cloud dataset indices. <br /></td></tr>
<tr class="separator:adb7ffc631b61dd54251b907d9b59c36b inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa1ad8057a457578023584ae099795133 inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="aa1ad8057a457578023584ae099795133"></a>
PointRepresentationConstPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#aa1ad8057a457578023584ae099795133">point_representation_</a></td></tr>
<tr class="memdesc:aa1ad8057a457578023584ae099795133 inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">The point representation used (internal). <br /></td></tr>
<tr class="separator:aa1ad8057a457578023584ae099795133 inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a106b60be21bde4d7ebaa257494d54481 inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="a106b60be21bde4d7ebaa257494d54481"></a>
PointCloudTargetPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a106b60be21bde4d7ebaa257494d54481">input_transformed_</a></td></tr>
<tr class="memdesc:a106b60be21bde4d7ebaa257494d54481 inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">The transformed input source point cloud dataset. <br /></td></tr>
<tr class="separator:a106b60be21bde4d7ebaa257494d54481 inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab05cddc8483c536b981712160ac368ce inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="ab05cddc8483c536b981712160ac368ce"></a>
std::vector&lt; <a class="el" href="structpcl_1_1_p_c_l_point_field.html">pcl::PCLPointField</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#ab05cddc8483c536b981712160ac368ce">input_fields_</a></td></tr>
<tr class="memdesc:ab05cddc8483c536b981712160ac368ce inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">The types of input point fields available. <br /></td></tr>
<tr class="separator:ab05cddc8483c536b981712160ac368ce inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac14f9ca285539bce5913e4e65cd8303f inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="ac14f9ca285539bce5913e4e65cd8303f"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#ac14f9ca285539bce5913e4e65cd8303f">target_cloud_updated_</a></td></tr>
<tr class="memdesc:ac14f9ca285539bce5913e4e65cd8303f inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Variable that stores whether we have a new target cloud, meaning we need to pre-process it again. This way, we avoid rebuilding the kd-tree for the target cloud every time the determineCorrespondences () method is called. <br /></td></tr>
<tr class="separator:ac14f9ca285539bce5913e4e65cd8303f inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a4c46a60269323a3bf665aac6397aee69 inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="a4c46a60269323a3bf665aac6397aee69"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a4c46a60269323a3bf665aac6397aee69">source_cloud_updated_</a></td></tr>
<tr class="memdesc:a4c46a60269323a3bf665aac6397aee69 inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Variable that stores whether we have a new source cloud, meaning we need to pre-process it again. This way, we avoid rebuilding the reciprocal kd-tree for the source cloud every time the determineCorrespondences () method is called. <br /></td></tr>
<tr class="separator:a4c46a60269323a3bf665aac6397aee69 inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:afae6e31f695321c118f61c59ea7571e4 inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="afae6e31f695321c118f61c59ea7571e4"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#afae6e31f695321c118f61c59ea7571e4">force_no_recompute_</a></td></tr>
<tr class="memdesc:afae6e31f695321c118f61c59ea7571e4 inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">A flag which, if set, means the tree operating on the target cloud will never be recomputed <br /></td></tr>
<tr class="separator:afae6e31f695321c118f61c59ea7571e4 inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:adb23b6a9f629bdc605cefeacea94bf14 inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memItemLeft" align="right" valign="top"><a id="adb23b6a9f629bdc605cefeacea94bf14"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#adb23b6a9f629bdc605cefeacea94bf14">force_no_recompute_reciprocal_</a></td></tr>
<tr class="memdesc:adb23b6a9f629bdc605cefeacea94bf14 inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">A flag which, if set, means the tree operating on the source cloud will never be recomputed <br /></td></tr>
<tr class="separator:adb23b6a9f629bdc605cefeacea94bf14 inherit pro_attribs_classpcl_1_1registration_1_1_correspondence_estimation_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pro_attribs_classpcl_1_1_p_c_l_base"><td colspan="2" onclick="javascript:toggleInherit('pro_attribs_classpcl_1_1_p_c_l_base')"><img src="closed.png" alt="-"/>&#160;Protected 属性 继承自 <a class="el" href="classpcl_1_1_p_c_l_base.html">pcl::PCLBase&lt; PointSource &gt;</a></td></tr>
<tr class="memitem:a09c70d8e06e3fb4f07903fe6f8d67869 inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="a09c70d8e06e3fb4f07903fe6f8d67869"></a>
PointCloudConstPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a></td></tr>
<tr class="memdesc:a09c70d8e06e3fb4f07903fe6f8d67869 inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">The input point cloud dataset. <br /></td></tr>
<tr class="separator:a09c70d8e06e3fb4f07903fe6f8d67869 inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aaee847c8a517ebf365bad2cb182a6626 inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="aaee847c8a517ebf365bad2cb182a6626"></a>
IndicesPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">indices_</a></td></tr>
<tr class="memdesc:aaee847c8a517ebf365bad2cb182a6626 inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">A pointer to the vector of point indices to use. <br /></td></tr>
<tr class="separator:aaee847c8a517ebf365bad2cb182a6626 inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ada1eadb824d34ca9206a86343d9760bb inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="ada1eadb824d34ca9206a86343d9760bb"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#ada1eadb824d34ca9206a86343d9760bb">use_indices_</a></td></tr>
<tr class="memdesc:ada1eadb824d34ca9206a86343d9760bb inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set to true if point indices are used. <br /></td></tr>
<tr class="separator:ada1eadb824d34ca9206a86343d9760bb inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:adadb0299f144528020ed558af6879662 inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="memItemLeft" align="right" valign="top"><a id="adadb0299f144528020ed558af6879662"></a>
bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_p_c_l_base.html#adadb0299f144528020ed558af6879662">fake_indices_</a></td></tr>
<tr class="memdesc:adadb0299f144528020ed558af6879662 inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="mdescLeft">&#160;</td><td class="mdescRight">If no set of indices are given, we construct a set of fake indices that mimic the input PointCloud. <br /></td></tr>
<tr class="separator:adadb0299f144528020ed558af6879662 inherit pro_attribs_classpcl_1_1_p_c_l_base"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table>
<a name="details" id="details"></a><h2 class="groupheader">详细描述</h2>
<div class="textblock"><h3>template&lt;typename PointSource, typename PointTarget, typename NormalT, typename Scalar = float&gt;<br />
class pcl::registration::CorrespondenceEstimationNormalShooting&lt; PointSource, PointTarget, NormalT, Scalar &gt;</h3>

<p><b><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html" title="CorrespondenceEstimationNormalShooting computes correspondences as points in the target cloud which h...">CorrespondenceEstimationNormalShooting</a></b> computes correspondences as points in the target cloud which have minimum distance to normals computed on the input cloud </p>
<p>Code example:</p>
<div class="fragment"><div class="line">pcl::PointCloud&lt;pcl::PointNormal&gt;::Ptr source, target;</div>
<div class="line"><span class="comment">// ... read or fill in source and target</span></div>
<div class="line">pcl::CorrespondenceEstimationNormalShooting&lt;pcl::PointNormal, pcl::PointNormal, pcl::PointNormal&gt; est;</div>
<div class="line">est.setInputSource (source);</div>
<div class="line">est.setSourceNormals (source);</div>
<div class="line"> </div>
<div class="line">est.setInputTarget (target);</div>
<div class="line"> </div>
<div class="line"><span class="comment">// Test the first 10 correspondences for each point in source, and return the best</span></div>
<div class="line">est.setKSearch (10);</div>
<div class="line"> </div>
<div class="line">pcl::Correspondences all_correspondences;</div>
<div class="line"><span class="comment">// Determine all correspondences</span></div>
<div class="line">est.determineCorrespondences (all_correspondences);</div>
</div><!-- fragment --><dl class="section author"><dt>作者</dt><dd>Aravindhan K. Krishnan, Radu B. Rusu </dd></dl>
</div><h2 class="groupheader">构造及析构函数说明</h2>
<a id="aae2aa6649dac6840562cf392d6c8fe8c"></a>
<h2 class="memtitle"><span class="permalink"><a href="#aae2aa6649dac6840562cf392d6c8fe8c">&#9670;&nbsp;</a></span>CorrespondenceEstimationNormalShooting()</h2>

<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;typename PointSource , typename PointTarget , typename NormalT , typename Scalar  = float&gt; </div>
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html">pcl::registration::CorrespondenceEstimationNormalShooting</a>&lt; PointSource, PointTarget, <a class="el" href="structpcl_1_1_normal.html">NormalT</a>, Scalar &gt;::<a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html">CorrespondenceEstimationNormalShooting</a> </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">inline</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Empty constructor. </p>
<dl class="section note"><dt>注解</dt><dd>Sets the number of neighbors to be considered in the target point cloud (k_) to 10. </dd></dl>
<div class="fragment"><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;          : <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a2ee2f0004f3cfd8463689c7c5f2cd5d6">source_normals_</a> ()</div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;          , <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a970b25748b2d88d9683594322b11e6de">source_normals_transformed_</a> ()</div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;          , <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a851e08a9f9c179228a59e39323bb9ca1">k_</a> (10)</div>
<div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;        {</div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;          <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#abafd815fa41e4762057c1351fa58c552">corr_name_</a> = <span class="stringliteral">&quot;CorrespondenceEstimationNormalShooting&quot;</span>;</div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;        }</div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_estimation_base_html_abafd815fa41e4762057c1351fa58c552"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#abafd815fa41e4762057c1351fa58c552">pcl::registration::CorrespondenceEstimationBase&lt; PointSource, PointTarget, float &gt;::corr_name_</a></div><div class="ttdeci">std::string corr_name_</div><div class="ttdoc">The correspondence estimation method name.</div><div class="ttdef"><b>Definition:</b> correspondence_estimation.h:301</div></div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_estimation_normal_shooting_html_a2ee2f0004f3cfd8463689c7c5f2cd5d6"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a2ee2f0004f3cfd8463689c7c5f2cd5d6">pcl::registration::CorrespondenceEstimationNormalShooting::source_normals_</a></div><div class="ttdeci">NormalsConstPtr source_normals_</div><div class="ttdoc">The normals computed at each point in the source cloud</div><div class="ttdef"><b>Definition:</b> correspondence_estimation_normal_shooting.h:208</div></div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_estimation_normal_shooting_html_a851e08a9f9c179228a59e39323bb9ca1"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a851e08a9f9c179228a59e39323bb9ca1">pcl::registration::CorrespondenceEstimationNormalShooting::k_</a></div><div class="ttdeci">unsigned int k_</div><div class="ttdoc">The number of neighbours to be considered in the target point cloud</div><div class="ttdef"><b>Definition:</b> correspondence_estimation_normal_shooting.h:214</div></div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_estimation_normal_shooting_html_a970b25748b2d88d9683594322b11e6de"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a970b25748b2d88d9683594322b11e6de">pcl::registration::CorrespondenceEstimationNormalShooting::source_normals_transformed_</a></div><div class="ttdeci">NormalsPtr source_normals_transformed_</div><div class="ttdoc">The normals computed at each point in the source cloud</div><div class="ttdef"><b>Definition:</b> correspondence_estimation_normal_shooting.h:211</div></div>
</div><!-- fragment -->
</div>
</div>
<h2 class="groupheader">成员函数说明</h2>
<a id="a348a50a8b8a0d3c5b14704d283ce068c"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a348a50a8b8a0d3c5b14704d283ce068c">&#9670;&nbsp;</a></span>determineCorrespondences()</h2>

<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;typename PointSource , typename PointTarget , typename NormalT , typename Scalar &gt; </div>
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html">pcl::registration::CorrespondenceEstimationNormalShooting</a>&lt; PointSource, PointTarget, <a class="el" href="structpcl_1_1_normal.html">NormalT</a>, Scalar &gt;::determineCorrespondences </td>
          <td>(</td>
          <td class="paramtype">pcl::Correspondences &amp;&#160;</td>
          <td class="paramname"><em>correspondences</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">double&#160;</td>
          <td class="paramname"><em>max_distance</em> = <code>std::numeric_limits&lt;double&gt;::max&#160;()</code>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">virtual</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Determine the correspondences between input and target cloud. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[out]</td><td class="paramname">correspondences</td><td>the found correspondences (index of query point, index of target point, distance) </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">max_distance</td><td>maximum distance between the normal on the source point cloud and the corresponding point in the target point cloud </td></tr>
  </table>
  </dd>
</dl>

<p>实现了 <a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#ad6545c8946e044093ef2e5373d347e27">pcl::registration::CorrespondenceEstimationBase&lt; PointSource, PointTarget, float &gt;</a>.</p>
<div class="fragment"><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;{</div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;  <span class="keywordflow">if</span> (!<a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#af979935c7f43038ab68ad6d0d701a801">initCompute</a> ())</div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160; </div>
<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;  correspondences.resize (<a class="code" href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">indices_</a>-&gt;size ());</div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160; </div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;  std::vector&lt;int&gt; nn_indices (<a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a851e08a9f9c179228a59e39323bb9ca1">k_</a>);</div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;  std::vector&lt;float&gt; nn_dists (<a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a851e08a9f9c179228a59e39323bb9ca1">k_</a>);</div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160; </div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;  <span class="keywordtype">double</span> min_dist = std::numeric_limits&lt;double&gt;::max ();</div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;  <span class="keywordtype">int</span> min_index = 0;</div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;  </div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;  <a class="code" href="structpcl_1_1_correspondence.html">pcl::Correspondence</a> corr;</div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> nr_valid_correspondences = 0;</div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160; </div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;  <span class="comment">// Check if the template types are the same. If true, avoid a copy.</span></div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;  <span class="comment">// Both point types MUST be registered using the POINT_CLOUD_REGISTER_POINT_STRUCT macro!</span></div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;  <span class="keywordflow">if</span> (isSamePointType&lt;PointSource, PointTarget&gt; ())</div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;  {</div>
<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;    PointTarget pt;</div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;    <span class="comment">// Iterate over the input set of source indices</span></div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;    <span class="keywordflow">for</span> (std::vector&lt;int&gt;::const_iterator idx_i = <a class="code" href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">indices_</a>-&gt;begin (); idx_i != <a class="code" href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">indices_</a>-&gt;end (); ++idx_i)</div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;    {</div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;      <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#ac43aa82c5e2d08b017639cc483d88ea2">tree_</a>-&gt;nearestKSearch (<a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a>-&gt;points[*idx_i], <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a851e08a9f9c179228a59e39323bb9ca1">k_</a>, nn_indices, nn_dists);</div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160; </div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;      <span class="comment">// Among the K nearest neighbours find the one with minimum perpendicular distance to the normal</span></div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;      min_dist = std::numeric_limits&lt;double&gt;::max ();</div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;      </div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;      <span class="comment">// Find the best correspondence</span></div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> j = 0; j &lt; nn_indices.size (); j++)</div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;      {</div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;        <span class="comment">// computing the distance between a point and a line in 3d. </span></div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;        <span class="comment">// Reference - http://mathworld.wolfram.com/Point-LineDistance3-Dimensional.html</span></div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;        pt.x = <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a269bd2ef4d241dc4dafebe6919e5650e">target_</a>-&gt;points[nn_indices[j]].x - <a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a>-&gt;points[*idx_i].x;</div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;        pt.y = <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a269bd2ef4d241dc4dafebe6919e5650e">target_</a>-&gt;points[nn_indices[j]].y - <a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a>-&gt;points[*idx_i].y;</div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;        pt.z = <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a269bd2ef4d241dc4dafebe6919e5650e">target_</a>-&gt;points[nn_indices[j]].z - <a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a>-&gt;points[*idx_i].z;</div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160; </div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;        <span class="keyword">const</span> <a class="code" href="structpcl_1_1_normal.html">NormalT</a> &amp;normal = <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a2ee2f0004f3cfd8463689c7c5f2cd5d6">source_normals_</a>-&gt;points[*idx_i];</div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;        Eigen::Vector3d N (normal.normal_x, normal.normal_y, normal.normal_z);</div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;        Eigen::Vector3d V (pt.x, pt.y, pt.z);</div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;        Eigen::Vector3d C = N.cross (V);</div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;        </div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;        <span class="comment">// Check if we have a better correspondence</span></div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;        <span class="keywordtype">double</span> dist = C.dot (C);</div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;        <span class="keywordflow">if</span> (dist &lt; min_dist)</div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;        {</div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;          min_dist = dist;</div>
<div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;          min_index = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (j);</div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;        }</div>
<div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;      }</div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;      <span class="keywordflow">if</span> (min_dist &gt; max_distance)</div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;        <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160; </div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;      corr.<a class="code" href="structpcl_1_1_correspondence.html#a1c5d6554ca02dd7aa34fa02f346e7399">index_query</a> = *idx_i;</div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;      corr.<a class="code" href="structpcl_1_1_correspondence.html#a5e5d2178826d203a755d37bfd317d701">index_match</a> = nn_indices[min_index];</div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;      corr.distance = nn_dists[min_index];<span class="comment">//min_dist;</span></div>
<div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;      correspondences[nr_valid_correspondences++] = corr;</div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;    }</div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;  }</div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;  {</div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;    PointTarget pt;</div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;    </div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;    <span class="comment">// Iterate over the input set of source indices</span></div>
<div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;    <span class="keywordflow">for</span> (std::vector&lt;int&gt;::const_iterator idx_i = <a class="code" href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">indices_</a>-&gt;begin (); idx_i != <a class="code" href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">indices_</a>-&gt;end (); ++idx_i)</div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;    {</div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;      <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#ac43aa82c5e2d08b017639cc483d88ea2">tree_</a>-&gt;nearestKSearch (<a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a>-&gt;points[*idx_i], <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a851e08a9f9c179228a59e39323bb9ca1">k_</a>, nn_indices, nn_dists);</div>
<div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160; </div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;      <span class="comment">// Among the K nearest neighbours find the one with minimum perpendicular distance to the normal</span></div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;      min_dist = std::numeric_limits&lt;double&gt;::max ();</div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;      </div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;      <span class="comment">// Find the best correspondence</span></div>
<div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> j = 0; j &lt; nn_indices.size (); j++)</div>
<div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;      {</div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;        PointSource pt_src;</div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;        <span class="comment">// Copy the source data to a target PointTarget format so we can search in the tree</span></div>
<div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;        <a class="code" href="group__common.html#gab978bf1754771246b2f140a5b52a8f8b">copyPoint</a> (<a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a>-&gt;points[*idx_i], pt_src);</div>
<div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160; </div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;        <span class="comment">// computing the distance between a point and a line in 3d. </span></div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;        <span class="comment">// Reference - http://mathworld.wolfram.com/Point-LineDistance3-Dimensional.html</span></div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;        pt.x = <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a269bd2ef4d241dc4dafebe6919e5650e">target_</a>-&gt;points[nn_indices[j]].x - pt_src.x;</div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;        pt.y = <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a269bd2ef4d241dc4dafebe6919e5650e">target_</a>-&gt;points[nn_indices[j]].y - pt_src.y;</div>
<div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;        pt.z = <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a269bd2ef4d241dc4dafebe6919e5650e">target_</a>-&gt;points[nn_indices[j]].z - pt_src.z;</div>
<div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;        </div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;        <span class="keyword">const</span> <a class="code" href="structpcl_1_1_normal.html">NormalT</a> &amp;normal = <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a2ee2f0004f3cfd8463689c7c5f2cd5d6">source_normals_</a>-&gt;points[*idx_i];</div>
<div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;        Eigen::Vector3d N (normal.normal_x, normal.normal_y, normal.normal_z);</div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;        Eigen::Vector3d V (pt.x, pt.y, pt.z);</div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;        Eigen::Vector3d C = N.cross (V);</div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;        </div>
<div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;        <span class="comment">// Check if we have a better correspondence</span></div>
<div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;        <span class="keywordtype">double</span> dist = C.dot (C);</div>
<div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;        <span class="keywordflow">if</span> (dist &lt; min_dist)</div>
<div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;        {</div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;          min_dist = dist;</div>
<div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;          min_index = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (j);</div>
<div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;        }</div>
<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;      }</div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;      <span class="keywordflow">if</span> (min_dist &gt; max_distance)</div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;        <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;      </div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;      corr.<a class="code" href="structpcl_1_1_correspondence.html#a1c5d6554ca02dd7aa34fa02f346e7399">index_query</a> = *idx_i;</div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;      corr.<a class="code" href="structpcl_1_1_correspondence.html#a5e5d2178826d203a755d37bfd317d701">index_match</a> = nn_indices[min_index];</div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;      corr.distance = nn_dists[min_index];<span class="comment">//min_dist;</span></div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;      correspondences[nr_valid_correspondences++] = corr;</div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;    }</div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;  }</div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;  correspondences.resize (nr_valid_correspondences);</div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;  <a class="code" href="classpcl_1_1_p_c_l_base.html#afc426c4eebb94b7734d4fa556bff1420">deinitCompute</a> ();</div>
<div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;}</div>
<div class="ttc" id="aclasspcl_1_1_p_c_l_base_html_a09c70d8e06e3fb4f07903fe6f8d67869"><div class="ttname"><a href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">pcl::PCLBase&lt; PointSource &gt;::input_</a></div><div class="ttdeci">PointCloudConstPtr input_</div><div class="ttdoc">The input point cloud dataset.</div><div class="ttdef"><b>Definition:</b> pcl_base.h:150</div></div>
<div class="ttc" id="aclasspcl_1_1_p_c_l_base_html_aaee847c8a517ebf365bad2cb182a6626"><div class="ttname"><a href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">pcl::PCLBase&lt; PointSource &gt;::indices_</a></div><div class="ttdeci">IndicesPtr indices_</div><div class="ttdoc">A pointer to the vector of point indices to use.</div><div class="ttdef"><b>Definition:</b> pcl_base.h:153</div></div>
<div class="ttc" id="aclasspcl_1_1_p_c_l_base_html_afc426c4eebb94b7734d4fa556bff1420"><div class="ttname"><a href="classpcl_1_1_p_c_l_base.html#afc426c4eebb94b7734d4fa556bff1420">pcl::PCLBase&lt; PointSource &gt;::deinitCompute</a></div><div class="ttdeci">bool deinitCompute()</div><div class="ttdoc">This method should get called after finishing the actual computation.</div><div class="ttdef"><b>Definition:</b> pcl_base.hpp:174</div></div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_estimation_base_html_a269bd2ef4d241dc4dafebe6919e5650e"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a269bd2ef4d241dc4dafebe6919e5650e">pcl::registration::CorrespondenceEstimationBase&lt; PointSource, PointTarget, float &gt;::target_</a></div><div class="ttdeci">PointCloudTargetConstPtr target_</div><div class="ttdoc">The input point cloud dataset target.</div><div class="ttdef"><b>Definition:</b> correspondence_estimation.h:312</div></div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_estimation_base_html_ac43aa82c5e2d08b017639cc483d88ea2"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#ac43aa82c5e2d08b017639cc483d88ea2">pcl::registration::CorrespondenceEstimationBase&lt; PointSource, PointTarget, float &gt;::tree_</a></div><div class="ttdeci">KdTreePtr tree_</div><div class="ttdoc">A pointer to the spatial search object used for the target dataset.</div><div class="ttdef"><b>Definition:</b> correspondence_estimation.h:304</div></div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_estimation_normal_shooting_html_af979935c7f43038ab68ad6d0d701a801"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#af979935c7f43038ab68ad6d0d701a801">pcl::registration::CorrespondenceEstimationNormalShooting::initCompute</a></div><div class="ttdeci">bool initCompute()</div><div class="ttdoc">Internal computation initalization.</div><div class="ttdef"><b>Definition:</b> correspondence_estimation_normal_shooting.hpp:47</div></div>
<div class="ttc" id="agroup__common_html_gab978bf1754771246b2f140a5b52a8f8b"><div class="ttname"><a href="group__common.html#gab978bf1754771246b2f140a5b52a8f8b">pcl::copyPoint</a></div><div class="ttdeci">void copyPoint(const PointInT &amp;point_in, PointOutT &amp;point_out)</div><div class="ttdoc">Copy the fields of a source point into a target point.</div><div class="ttdef"><b>Definition:</b> copy_point.hpp:138</div></div>
<div class="ttc" id="astructpcl_1_1_correspondence_html"><div class="ttname"><a href="structpcl_1_1_correspondence.html">pcl::Correspondence</a></div><div class="ttdoc">Correspondence represents a match between two entities (e.g., points, descriptors,...</div><div class="ttdef"><b>Definition:</b> correspondence.h:59</div></div>
<div class="ttc" id="astructpcl_1_1_correspondence_html_a1c5d6554ca02dd7aa34fa02f346e7399"><div class="ttname"><a href="structpcl_1_1_correspondence.html#a1c5d6554ca02dd7aa34fa02f346e7399">pcl::Correspondence::index_query</a></div><div class="ttdeci">int index_query</div><div class="ttdoc">Index of the query (source) point.</div><div class="ttdef"><b>Definition:</b> correspondence.h:61</div></div>
<div class="ttc" id="astructpcl_1_1_correspondence_html_a5e5d2178826d203a755d37bfd317d701"><div class="ttname"><a href="structpcl_1_1_correspondence.html#a5e5d2178826d203a755d37bfd317d701">pcl::Correspondence::index_match</a></div><div class="ttdeci">int index_match</div><div class="ttdoc">Index of the matching (target) point. Set to -1 if no correspondence found.</div><div class="ttdef"><b>Definition:</b> correspondence.h:63</div></div>
<div class="ttc" id="astructpcl_1_1_normal_html"><div class="ttname"><a href="structpcl_1_1_normal.html">pcl::Normal</a></div><div class="ttdoc">A point structure representing normal coordinates and the surface curvature estimate....</div><div class="ttdef"><b>Definition:</b> point_types.hpp:779</div></div>
</div><!-- fragment -->
</div>
</div>
<a id="a93c946684ceff4a5686852be95852835"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a93c946684ceff4a5686852be95852835">&#9670;&nbsp;</a></span>determineReciprocalCorrespondences()</h2>

<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;typename PointSource , typename PointTarget , typename NormalT , typename Scalar &gt; </div>
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html">pcl::registration::CorrespondenceEstimationNormalShooting</a>&lt; PointSource, PointTarget, <a class="el" href="structpcl_1_1_normal.html">NormalT</a>, Scalar &gt;::determineReciprocalCorrespondences </td>
          <td>(</td>
          <td class="paramtype">pcl::Correspondences &amp;&#160;</td>
          <td class="paramname"><em>correspondences</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">double&#160;</td>
          <td class="paramname"><em>max_distance</em> = <code>std::numeric_limits&lt;double&gt;::max&#160;()</code>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">virtual</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Determine the reciprocal correspondences between input and target cloud. A correspondence is considered reciprocal if both Src_i has Tgt_i as a correspondence, and Tgt_i has Src_i as one. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[out]</td><td class="paramname">correspondences</td><td>the found correspondences (index of query and target point, distance) </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">max_distance</td><td>maximum allowed distance between correspondences </td></tr>
  </table>
  </dd>
</dl>

<p>实现了 <a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a3c21cd891d7df337648dc05d71008be2">pcl::registration::CorrespondenceEstimationBase&lt; PointSource, PointTarget, float &gt;</a>.</p>
<div class="fragment"><div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;{</div>
<div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;  <span class="keywordflow">if</span> (!<a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#af979935c7f43038ab68ad6d0d701a801">initCompute</a> ())</div>
<div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160; </div>
<div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;  <span class="comment">// setup tree for reciprocal search</span></div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;  <span class="comment">// Set the internal point representation of choice</span></div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;  <span class="keywordflow">if</span> (!<a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#ad7afb551d656990f5caf03ba2fc5f6c0">initComputeReciprocal</a> ())</div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160; </div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;  correspondences.resize (<a class="code" href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">indices_</a>-&gt;size ());</div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160; </div>
<div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;  std::vector&lt;int&gt; nn_indices (<a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a851e08a9f9c179228a59e39323bb9ca1">k_</a>);</div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;  std::vector&lt;float&gt; nn_dists (<a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a851e08a9f9c179228a59e39323bb9ca1">k_</a>);</div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;  std::vector&lt;int&gt; index_reciprocal (1);</div>
<div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;  std::vector&lt;float&gt; distance_reciprocal (1);</div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160; </div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;  <span class="keywordtype">double</span> min_dist = std::numeric_limits&lt;double&gt;::max ();</div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;  <span class="keywordtype">int</span> min_index = 0;</div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;  </div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;  <a class="code" href="structpcl_1_1_correspondence.html">pcl::Correspondence</a> corr;</div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> nr_valid_correspondences = 0;</div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;  <span class="keywordtype">int</span> target_idx = 0;</div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160; </div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;  <span class="comment">// Check if the template types are the same. If true, avoid a copy.</span></div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;  <span class="comment">// Both point types MUST be registered using the POINT_CLOUD_REGISTER_POINT_STRUCT macro!</span></div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;  <span class="keywordflow">if</span> (isSamePointType&lt;PointSource, PointTarget&gt; ())</div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;  {</div>
<div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;    PointTarget pt;</div>
<div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;    <span class="comment">// Iterate over the input set of source indices</span></div>
<div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;    <span class="keywordflow">for</span> (std::vector&lt;int&gt;::const_iterator idx_i = <a class="code" href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">indices_</a>-&gt;begin (); idx_i != <a class="code" href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">indices_</a>-&gt;end (); ++idx_i)</div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;    {</div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;      <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#ac43aa82c5e2d08b017639cc483d88ea2">tree_</a>-&gt;nearestKSearch (<a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a>-&gt;points[*idx_i], <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a851e08a9f9c179228a59e39323bb9ca1">k_</a>, nn_indices, nn_dists);</div>
<div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160; </div>
<div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;      <span class="comment">// Among the K nearest neighbours find the one with minimum perpendicular distance to the normal</span></div>
<div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;      min_dist = std::numeric_limits&lt;double&gt;::max ();</div>
<div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;      </div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;      <span class="comment">// Find the best correspondence</span></div>
<div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> j = 0; j &lt; nn_indices.size (); j++)</div>
<div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;      {</div>
<div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;        <span class="comment">// computing the distance between a point and a line in 3d. </span></div>
<div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;        <span class="comment">// Reference - http://mathworld.wolfram.com/Point-LineDistance3-Dimensional.html</span></div>
<div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;        pt.x = <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a269bd2ef4d241dc4dafebe6919e5650e">target_</a>-&gt;points[nn_indices[j]].x - <a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a>-&gt;points[*idx_i].x;</div>
<div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;        pt.y = <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a269bd2ef4d241dc4dafebe6919e5650e">target_</a>-&gt;points[nn_indices[j]].y - <a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a>-&gt;points[*idx_i].y;</div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;        pt.z = <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a269bd2ef4d241dc4dafebe6919e5650e">target_</a>-&gt;points[nn_indices[j]].z - <a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a>-&gt;points[*idx_i].z;</div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160; </div>
<div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;        <span class="keyword">const</span> <a class="code" href="structpcl_1_1_normal.html">NormalT</a> &amp;normal = <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a2ee2f0004f3cfd8463689c7c5f2cd5d6">source_normals_</a>-&gt;points[*idx_i];</div>
<div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;        Eigen::Vector3d N (normal.normal_x, normal.normal_y, normal.normal_z);</div>
<div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;        Eigen::Vector3d V (pt.x, pt.y, pt.z);</div>
<div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;        Eigen::Vector3d C = N.cross (V);</div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;        </div>
<div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;        <span class="comment">// Check if we have a better correspondence</span></div>
<div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;        <span class="keywordtype">double</span> dist = C.dot (C);</div>
<div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;        <span class="keywordflow">if</span> (dist &lt; min_dist)</div>
<div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;        {</div>
<div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;          min_dist = dist;</div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;          min_index = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (j);</div>
<div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;        }</div>
<div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;      }</div>
<div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;      <span class="keywordflow">if</span> (min_dist &gt; max_distance)</div>
<div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;        <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160; </div>
<div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;      <span class="comment">// Check if the correspondence is reciprocal</span></div>
<div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;      target_idx = nn_indices[min_index];</div>
<div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;      <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#ad15e1f9630bc3bb5e5c412dc8e9183ff">tree_reciprocal_</a>-&gt;nearestKSearch (<a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a269bd2ef4d241dc4dafebe6919e5650e">target_</a>-&gt;points[target_idx], 1, index_reciprocal, distance_reciprocal);</div>
<div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160; </div>
<div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;      <span class="keywordflow">if</span> (*idx_i != index_reciprocal[0])</div>
<div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;        <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160; </div>
<div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;      <span class="comment">// Correspondence IS reciprocal, save it and continue</span></div>
<div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;      corr.<a class="code" href="structpcl_1_1_correspondence.html#a1c5d6554ca02dd7aa34fa02f346e7399">index_query</a> = *idx_i;</div>
<div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;      corr.<a class="code" href="structpcl_1_1_correspondence.html#a5e5d2178826d203a755d37bfd317d701">index_match</a> = nn_indices[min_index];</div>
<div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;      corr.distance = nn_dists[min_index];<span class="comment">//min_dist;</span></div>
<div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;      correspondences[nr_valid_correspondences++] = corr;</div>
<div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;    }</div>
<div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;  }</div>
<div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;  {</div>
<div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;    PointTarget pt;</div>
<div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;    </div>
<div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;    <span class="comment">// Iterate over the input set of source indices</span></div>
<div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;    <span class="keywordflow">for</span> (std::vector&lt;int&gt;::const_iterator idx_i = <a class="code" href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">indices_</a>-&gt;begin (); idx_i != <a class="code" href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">indices_</a>-&gt;end (); ++idx_i)</div>
<div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;    {</div>
<div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;      <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#ac43aa82c5e2d08b017639cc483d88ea2">tree_</a>-&gt;nearestKSearch (<a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a>-&gt;points[*idx_i], <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a851e08a9f9c179228a59e39323bb9ca1">k_</a>, nn_indices, nn_dists);</div>
<div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160; </div>
<div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;      <span class="comment">// Among the K nearest neighbours find the one with minimum perpendicular distance to the normal</span></div>
<div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;      min_dist = std::numeric_limits&lt;double&gt;::max ();</div>
<div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;      </div>
<div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;      <span class="comment">// Find the best correspondence</span></div>
<div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> j = 0; j &lt; nn_indices.size (); j++)</div>
<div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;      {</div>
<div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;        PointSource pt_src;</div>
<div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;        <span class="comment">// Copy the source data to a target PointTarget format so we can search in the tree</span></div>
<div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;        <a class="code" href="group__common.html#gab978bf1754771246b2f140a5b52a8f8b">copyPoint</a> (<a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a>-&gt;points[*idx_i], pt_src);</div>
<div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160; </div>
<div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;        <span class="comment">// computing the distance between a point and a line in 3d. </span></div>
<div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;        <span class="comment">// Reference - http://mathworld.wolfram.com/Point-LineDistance3-Dimensional.html</span></div>
<div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;        pt.x = <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a269bd2ef4d241dc4dafebe6919e5650e">target_</a>-&gt;points[nn_indices[j]].x - pt_src.x;</div>
<div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;        pt.y = <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a269bd2ef4d241dc4dafebe6919e5650e">target_</a>-&gt;points[nn_indices[j]].y - pt_src.y;</div>
<div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;        pt.z = <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a269bd2ef4d241dc4dafebe6919e5650e">target_</a>-&gt;points[nn_indices[j]].z - pt_src.z;</div>
<div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;        </div>
<div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;        <span class="keyword">const</span> <a class="code" href="structpcl_1_1_normal.html">NormalT</a> &amp;normal = <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a2ee2f0004f3cfd8463689c7c5f2cd5d6">source_normals_</a>-&gt;points[*idx_i];</div>
<div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;        Eigen::Vector3d N (normal.normal_x, normal.normal_y, normal.normal_z);</div>
<div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;        Eigen::Vector3d V (pt.x, pt.y, pt.z);</div>
<div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;        Eigen::Vector3d C = N.cross (V);</div>
<div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;        </div>
<div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;        <span class="comment">// Check if we have a better correspondence</span></div>
<div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;        <span class="keywordtype">double</span> dist = C.dot (C);</div>
<div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;        <span class="keywordflow">if</span> (dist &lt; min_dist)</div>
<div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;        {</div>
<div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;          min_dist = dist;</div>
<div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;          min_index = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (j);</div>
<div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;        }</div>
<div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;      }</div>
<div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;      <span class="keywordflow">if</span> (min_dist &gt; max_distance)</div>
<div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;        <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160; </div>
<div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;      <span class="comment">// Check if the correspondence is reciprocal</span></div>
<div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;      target_idx = nn_indices[min_index];</div>
<div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;      <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#ad15e1f9630bc3bb5e5c412dc8e9183ff">tree_reciprocal_</a>-&gt;nearestKSearch (<a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#a269bd2ef4d241dc4dafebe6919e5650e">target_</a>-&gt;points[target_idx], 1, index_reciprocal, distance_reciprocal);</div>
<div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160; </div>
<div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;      <span class="keywordflow">if</span> (*idx_i != index_reciprocal[0])</div>
<div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;        <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160; </div>
<div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;      <span class="comment">// Correspondence IS reciprocal, save it and continue</span></div>
<div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;      corr.<a class="code" href="structpcl_1_1_correspondence.html#a1c5d6554ca02dd7aa34fa02f346e7399">index_query</a> = *idx_i;</div>
<div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;      corr.<a class="code" href="structpcl_1_1_correspondence.html#a5e5d2178826d203a755d37bfd317d701">index_match</a> = nn_indices[min_index];</div>
<div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;      corr.distance = nn_dists[min_index];<span class="comment">//min_dist;</span></div>
<div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;      correspondences[nr_valid_correspondences++] = corr;</div>
<div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;    }</div>
<div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;  }</div>
<div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;  correspondences.resize (nr_valid_correspondences);</div>
<div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;  <a class="code" href="classpcl_1_1_p_c_l_base.html#afc426c4eebb94b7734d4fa556bff1420">deinitCompute</a> ();</div>
<div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;}</div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_estimation_base_html_ad15e1f9630bc3bb5e5c412dc8e9183ff"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#ad15e1f9630bc3bb5e5c412dc8e9183ff">pcl::registration::CorrespondenceEstimationBase&lt; PointSource, PointTarget, float &gt;::tree_reciprocal_</a></div><div class="ttdeci">KdTreeReciprocalPtr tree_reciprocal_</div><div class="ttdoc">A pointer to the spatial search object used for the source dataset.</div><div class="ttdef"><b>Definition:</b> correspondence_estimation.h:307</div></div>
<div class="ttc" id="aclasspcl_1_1registration_1_1_correspondence_estimation_base_html_ad7afb551d656990f5caf03ba2fc5f6c0"><div class="ttname"><a href="classpcl_1_1registration_1_1_correspondence_estimation_base.html#ad7afb551d656990f5caf03ba2fc5f6c0">pcl::registration::CorrespondenceEstimationBase&lt; PointSource, PointTarget, float &gt;::initComputeReciprocal</a></div><div class="ttdeci">bool initComputeReciprocal()</div><div class="ttdoc">Internal computation initalization for reciprocal correspondences.</div><div class="ttdef"><b>Definition:</b> correspondence_estimation.hpp:106</div></div>
</div><!-- fragment -->
</div>
</div>
<a id="a6a9dba31ba0d0be3a2befe13a56a5f5a"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a6a9dba31ba0d0be3a2befe13a56a5f5a">&#9670;&nbsp;</a></span>setKSearch()</h2>

<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;typename PointSource , typename PointTarget , typename NormalT , typename Scalar  = float&gt; </div>
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html">pcl::registration::CorrespondenceEstimationNormalShooting</a>&lt; PointSource, PointTarget, <a class="el" href="structpcl_1_1_normal.html">NormalT</a>, Scalar &gt;::setKSearch </td>
          <td>(</td>
          <td class="paramtype">unsigned int&#160;</td>
          <td class="paramname"><em>k</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">inline</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Set the number of nearest neighbours to be considered in the target point cloud. By default, we use k = 10 nearest neighbors. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">k</td><td>the number of nearest neighbours to be considered </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;{ <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a851e08a9f9c179228a59e39323bb9ca1">k_</a> = k; }</div>
</div><!-- fragment -->
</div>
</div>
<a id="af651fe7489cf7cab8eb622e1d77f642e"></a>
<h2 class="memtitle"><span class="permalink"><a href="#af651fe7489cf7cab8eb622e1d77f642e">&#9670;&nbsp;</a></span>setSourceNormals()</h2>

<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;typename PointSource , typename PointTarget , typename NormalT , typename Scalar  = float&gt; </div>
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html">pcl::registration::CorrespondenceEstimationNormalShooting</a>&lt; PointSource, PointTarget, <a class="el" href="structpcl_1_1_normal.html">NormalT</a>, Scalar &gt;::setSourceNormals </td>
          <td>(</td>
          <td class="paramtype">const NormalsConstPtr &amp;&#160;</td>
          <td class="paramname"><em>normals</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">inline</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Set the normals computed on the source point cloud </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">normals</td><td>the normals computed for the source cloud </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;{ <a class="code" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html#a2ee2f0004f3cfd8463689c7c5f2cd5d6">source_normals_</a> = normals; }</div>
</div><!-- fragment -->
</div>
</div>
<hr/>该类的文档由以下文件生成:<ul>
<li>registration/include/pcl/registration/<a class="el" href="correspondence__estimation__normal__shooting_8h_source.html">correspondence_estimation_normal_shooting.h</a></li>
<li>registration/include/pcl/registration/impl/<a class="el" href="correspondence__estimation__normal__shooting_8hpp_source.html">correspondence_estimation_normal_shooting.hpp</a></li>
</ul>
</div><!-- contents -->
</div><!-- doc-content -->
<!-- start footer part -->
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
  <ul>
    <li class="navelem"><b>pcl</b></li><li class="navelem"><b>registration</b></li><li class="navelem"><a class="el" href="classpcl_1_1registration_1_1_correspondence_estimation_normal_shooting.html">CorrespondenceEstimationNormalShooting</a></li>
    <li class="footer">制作者 <a href="https://www.doxygen.org/index.html"><img class="footer" src="doxygen.svg" width="104" height="31" alt="doxygen"/></a> 1.9.1 </li>
  </ul>
</div>
</body>
</html>
